{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"http://hilpisch.com/tpq_logo.png\" alt=\"The Python Quants\" width=\"45%\" align=\"right\" border=\"4\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Stochastic Short Rates"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This brief section illustrates the use of stochastic short rate models for simulation and (risk-neutral) discounting. The class used is called `stochastic_short_rate`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The Modelling "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, the market environment. As a stochastic short rate model the `square_root_diffusion` class is (currently) available. We therefore need to define the respective parameters for this class in the market environment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dx import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "me = market_environment(name='me', pricing_date=dt.datetime(2015, 1, 1))\n",
    "me.add_constant('initial_value', 0.01)\n",
    "me.add_constant('volatility', 0.1)\n",
    "me.add_constant('kappa', 2.0)\n",
    "me.add_constant('theta', 0.05)\n",
    "me.add_constant('paths', 1000)\n",
    "me.add_constant('frequency', 'M')\n",
    "me.add_constant('starting_date', me.pricing_date)\n",
    "me.add_constant('final_date', dt.datetime(2015, 12, 31))\n",
    "me.add_curve('discount_curve', 0.0)  # dummy\n",
    "me.add_constant('currency', 0.0)  # dummy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Second, the instantiation of the class."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "ssr = stochastic_short_rate('sr', me)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following is an example `list` object containing `datetime` objects."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "time_list = [dt.datetime(2015, 1, 1),\n",
    "             dt.datetime(2015, 4, 1),\n",
    "             dt.datetime(2015, 6, 15),\n",
    "             dt.datetime(2015, 10, 21)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The call of the method `get_forward_reates()` yields the above `time_list` object and the simulated forward rates. In this case, 10 simulations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([datetime.datetime(2015, 1, 1, 0, 0),\n",
       "  datetime.datetime(2015, 4, 1, 0, 0),\n",
       "  datetime.datetime(2015, 6, 15, 0, 0),\n",
       "  datetime.datetime(2015, 10, 21, 0, 0)],\n",
       " array([[0.01      , 0.01      , 0.01      , 0.01      , 0.01      ,\n",
       "         0.01      , 0.01      , 0.01      , 0.01      , 0.01      ],\n",
       "        [0.03277202, 0.02888579, 0.02597219, 0.03437966, 0.02609197,\n",
       "         0.02668004, 0.03056627, 0.03347986, 0.02507239, 0.03336008],\n",
       "        [0.04847622, 0.02778153, 0.02208502, 0.03542504, 0.03381398,\n",
       "         0.02848213, 0.04861457, 0.05589349, 0.03990585, 0.04257658],\n",
       "        [0.05166403, 0.04121302, 0.05144506, 0.06797319, 0.02824299,\n",
       "         0.0419498 , 0.05243283, 0.03619928, 0.02328994, 0.06677311]]))"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ssr.get_forward_rates(time_list, 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Accordingly, the call of the `get_discount_factors()` method yields simulated zero-coupon bond prices for the time grid."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([datetime.datetime(2015, 1, 1, 0, 0),\n",
       "  datetime.datetime(2015, 4, 1, 0, 0),\n",
       "  datetime.datetime(2015, 6, 15, 0, 0),\n",
       "  datetime.datetime(2015, 10, 21, 0, 0)],\n",
       " array([[0.96930155, 0.97754222, 0.97798078, 0.9696954 , 0.97874354,\n",
       "         0.97771286, 0.96961689, 0.96977567, 0.97816125, 0.96819563],\n",
       "        [0.97442643, 0.98223994, 0.98232769, 0.97501559, 0.98310835,\n",
       "         0.98214428, 0.97447841, 0.97498814, 0.98239997, 0.97338523],\n",
       "        [0.98259442, 0.98797521, 0.98718981, 0.98203326, 0.98917777,\n",
       "         0.98772624, 0.98243814, 0.9839819 , 0.98898026, 0.981009  ],\n",
       "        [1.        , 1.        , 1.        , 1.        , 1.        ,\n",
       "         1.        , 1.        , 1.        , 1.        , 1.        ]]))"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ssr.get_discount_factors(time_list, 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Stochstic Drifts"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us value use the stochastic short rate model to simulate a geometric Brownian motion with stochastic short rate. Define the market environment as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "me.add_constant('initial_value', 36.)\n",
    "me.add_constant('volatility', 0.2)\n",
    "  # time horizon for the simulation\n",
    "me.add_constant('currency', 'EUR')\n",
    "me.add_constant('frequency', 'M')\n",
    "  # monthly frequency; paramter accorind to pandas convention\n",
    "me.add_constant('paths', 10)\n",
    "  # number of paths for simulation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then add the `stochastic_short_rate` object as discount curve."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "me.add_curve('discount_curve', ssr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, instantiate the `geometric_brownian_motion` object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "gbm = geometric_brownian_motion('gbm', me)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We get simulated instrument values as usual via the `get_instrument_values()` method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[36.        , 36.        , 36.        , 36.        , 36.        ,\n",
       "        36.        , 36.        , 36.        , 36.        , 36.        ],\n",
       "       [36.8060297 , 35.75560124, 34.98778226, 37.24953986, 35.01902026,\n",
       "        35.17279091, 36.20609756, 37.00065288, 34.75400748, 36.96764721],\n",
       "       [38.21614839, 34.16569133, 32.70350696, 36.40954077, 34.65561565,\n",
       "        33.87070953, 37.88603564, 39.58040249, 35.55090852, 37.35044144],\n",
       "       [38.47450027, 33.88999526, 34.0982215 , 39.27489627, 32.69322908,\n",
       "        33.66728041, 38.22119959, 37.9877562 , 32.97984662, 39.62076877],\n",
       "       [37.76574157, 33.70921262, 34.93754066, 41.4857547 , 33.30286899,\n",
       "        34.3470077 , 38.48001428, 37.12512733, 31.26650887, 38.95014155],\n",
       "       [41.40824335, 32.65237919, 34.18828508, 39.57699414, 36.64649108,\n",
       "        31.39011407, 39.80780981, 38.01482674, 32.84186281, 35.46744615],\n",
       "       [41.32002568, 32.83888512, 33.57945454, 39.52883894, 36.05892171,\n",
       "        31.53555452, 39.68092784, 38.79866413, 32.96181069, 36.13177382],\n",
       "       [46.41216195, 32.72457065, 32.48000699, 35.96872893, 38.02757568,\n",
       "        28.16218767, 39.93935721, 40.23115152, 36.33000552, 34.36135112],\n",
       "       [43.76336092, 34.05939936, 38.16985125, 37.76248586, 35.7087264 ,\n",
       "        29.96841401, 38.50269177, 34.34515834, 34.71596345, 36.71192144],\n",
       "       [43.41102129, 33.28842046, 37.53369604, 35.44705255, 34.25211077,\n",
       "        30.3159961 , 39.53272861, 35.04339421, 37.10939043, 38.4034044 ],\n",
       "       [50.70091956, 35.54130837, 33.67719457, 34.15617789, 36.58057258,\n",
       "        26.05844606, 37.16975856, 39.1972456 , 38.65893079, 36.09388287],\n",
       "       [51.40881852, 33.92751964, 30.54827552, 36.53604564, 38.97303122,\n",
       "        25.80445233, 39.08967422, 43.37205968, 36.28052847, 34.0082156 ],\n",
       "       [45.46321155, 31.21544356, 30.90125559, 39.76590057, 39.76247076,\n",
       "        29.30040939, 42.66414473, 43.05146618, 33.47040857, 33.47267446]])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gbm.get_instrument_values()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  Visualization of Simulated Stochastic Short Rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pylab import plt\n",
    "plt.style.use('seaborn')\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAlcAAAFkCAYAAAANPR4aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nALaQTJwdSzT1AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x109960208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# short rate paths\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.plot(ssr.process.instrument_values[:, :10]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Copyright, License & Disclaimer**\n",
    "\n",
    "© Dr. Yves J. Hilpisch | The Python Quants GmbH\n",
    "\n",
    "DX Analytics (the \"dx library\" or \"dx package\") is licensed under the GNU Affero General\n",
    "Public License version 3 or later (see http://www.gnu.org/licenses/).\n",
    "\n",
    "DX Analytics comes with no representations or warranties, to the extent\n",
    "permitted by applicable law.\n",
    "\n",
    "http://tpq.io | [dx@tpq.io](mailto:team@tpq.io) |\n",
    "http://twitter.com/dyjh\n",
    "\n",
    "<img src=\"http://hilpisch.com/tpq_logo.png\" alt=\"The Python Quants\" width=\"35%\" align=\"right\" border=\"0\"><br>\n",
    "\n",
    "**Quant Platform** | http://pqp.io\n",
    "\n",
    "**Python for Finance Training** | http://training.tpq.io\n",
    "\n",
    "**Certificate in Computational Finance** | http://compfinance.tpq.io\n",
    "\n",
    "**Derivatives Analytics with Python (Wiley Finance)** |\n",
    "http://dawp.tpq.io\n",
    "\n",
    "**Python for Finance (2nd ed., O'Reilly)** |\n",
    "http://py4fi.tpq.io"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
